Pricing for Past Channel State Information in Multi-Channel Cognitive Radio Networks

Sunjung Kang; Changhee Joo; Joohyun Lee; Ness B. Shroff

doi:10.1109/TMC.2017.2740931

Pricing for Past Channel State Information in Multi-Channel Cognitive Radio Networks

Sunjung Kang, Changhee Joo, Joohyun Lee, Ness B. Shroff

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

Cognitive Radio (CR) networks have received significant attention as a promising approach to improve the spectrum efficiency of current license-based regulatory system. In CR networks, a Secondary User (SU) can use a spectrum vacancy that can be detected by either sensing-before-transmission or database access. However, it is often difficult to detect a vacant spectrum opportunity because of inaccuracies due to sensing and delays to update and/or the database that holds this information. In this paper, we develop a hybrid detection framework in multi-channel CR networks, where an SU can selectively sense a channel for spectrum vacancy by accessing the spectrum history of Markovian channels. We focus on the value of the channel history information offered by the Primary Provider (PP) of each channel, and consider a market for the information exchange between multiple PPs and SUs. We investigate the interplay between of the PPs and the SUs through their pricing and buying decisions for this information, in the presence of sensing inaccuracy, i.e., false alarm and miss detection.

Original language	English
Pages (from-to)	859-870
Number of pages	12
Journal	IEEE Transactions on Mobile Computing
Volume	17
Issue number	4
DOIs	https://doi.org/10.1109/TMC.2017.2740931
Publication status	Published - 2018 Apr 1
Externally published	Yes

Bibliographical note

Funding Information:
This work was supported in part by IITP grant funded by the Korea government (MSIT) (No. 2015-0-00278, Research on Near-Zero Latency Network for 5G Immersive Service), and in part by NSF grants CNS-1421576, CNS-1409336, CNS-1446582, and the Office of Naval Research (ONR) grant N00014-15-1-2166. An earlier version of the work appeared at WiOpt 2016 [1].

Publisher Copyright:
© 2002-2012 IEEE.

Keywords

Cognitive radio
Gilbert-Elliott channel model
Network economics
Pricing
Stackelberg game

ASJC Scopus subject areas

Software
Computer Networks and Communications
Electrical and Electronic Engineering

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10.1109/TMC.2017.2740931

Cite this

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abstract = "Cognitive Radio (CR) networks have received significant attention as a promising approach to improve the spectrum efficiency of current license-based regulatory system. In CR networks, a Secondary User (SU) can use a spectrum vacancy that can be detected by either sensing-before-transmission or database access. However, it is often difficult to detect a vacant spectrum opportunity because of inaccuracies due to sensing and delays to update and/or the database that holds this information. In this paper, we develop a hybrid detection framework in multi-channel CR networks, where an SU can selectively sense a channel for spectrum vacancy by accessing the spectrum history of Markovian channels. We focus on the value of the channel history information offered by the Primary Provider (PP) of each channel, and consider a market for the information exchange between multiple PPs and SUs. We investigate the interplay between of the PPs and the SUs through their pricing and buying decisions for this information, in the presence of sensing inaccuracy, i.e., false alarm and miss detection.",

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N2 - Cognitive Radio (CR) networks have received significant attention as a promising approach to improve the spectrum efficiency of current license-based regulatory system. In CR networks, a Secondary User (SU) can use a spectrum vacancy that can be detected by either sensing-before-transmission or database access. However, it is often difficult to detect a vacant spectrum opportunity because of inaccuracies due to sensing and delays to update and/or the database that holds this information. In this paper, we develop a hybrid detection framework in multi-channel CR networks, where an SU can selectively sense a channel for spectrum vacancy by accessing the spectrum history of Markovian channels. We focus on the value of the channel history information offered by the Primary Provider (PP) of each channel, and consider a market for the information exchange between multiple PPs and SUs. We investigate the interplay between of the PPs and the SUs through their pricing and buying decisions for this information, in the presence of sensing inaccuracy, i.e., false alarm and miss detection.

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Pricing for Past Channel State Information in Multi-Channel Cognitive Radio Networks

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Keywords

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